Abstract
Abstract The objective of this work was to compare ordinary kriging with regression kriging to map soil properties at different depths in a tropical dry forest area in Brazil. The 11 soil properties evaluated were: organic carbon content and stock; bulk density; clay, sand, and silt contents; cation exchange capacity; pH; water retention at field capacity and at permanent wilting point; and available water. Samples were taken from 327 sites at 0.0-0.10, 0.10-0.20, and 0.20-0.40-m depths, in a tropical dry forest area of 102 km2. Stepwise linear regression models for particle-size fractions and water retention properties had the best fit. Relief and parent material covariates were selected in 31 of the 33 models (11 properties at three depths) and vegetation covariates in 29 models. Based on external validation, ordinary kriging obtained higher accuracy for 21 out of 33 property x depth combinations, indicating that the inclusion of a linear trend model before kriging does not necessarily improve predictions. Therefore, for similar studies, the geostatistical methods employed should be compared on a case-by-case basis.
Highlights
Tropical dry forests correspond to 42% of the world’s tropical and subtropical forests (Murphy & Lugo, 1986), of which about 54% occur in South America (Miles et al, 2006)
The objective of this work was to compare ordinary kriging with regression kriging to map soil properties at different depths in a tropical dry forest area in Brazil
The study was conducted at Parque Estadual da Mata Seca, a dry forest state park, in the north of the state of Minas Gerais, Brazil (43°58'48"W, 14°52'12"S) (Figure 1)
Summary
Tropical dry forests correspond to 42% of the world’s tropical and subtropical forests (Murphy & Lugo, 1986), of which about 54% occur in South America (Miles et al, 2006). In Brazil, and possibly other tropical countries, laws concerning tropical dry forests are ill-defined, grouping them with moister or drier forest types This creates a conundrum, hindering the proper conservation of this important ecosystem that serves as a habitat for many endemic species, as well as a food and wood source for traditional peoples, but is still little studied. Soil maps can be used to provide information to support government and private sector decisions for promoting the use and conservation of this poorly-known, threatened ecosystem and for guiding future research (Miles et al, 2006). Soils vary both horizontally and vertically in the landscape, and are continuously modified by internal. While the former assumes uniformity within mapping units and abrupt changes at their boundaries, the latter assumes that all variation is gradual; in reality, soil properties may present both gradual and abrupt changes spatially
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
